Dynamic Programing based Maintenance and Replacement Optimization for Bridge Decks using History-Dependent Deterioration Models
In this research, a reliability-based optimization model of bridge maintenance and replacement decisions is developed. Bridge maintenance optimization models use deterioration models to predict the future condition of bridges. Some current optimization models use physically-based models taking into account the history of deterioration. However, due to the complexity of the deterioration models, the number of decision variables in these optimization models is limited. Some other optimization models consist of a full set of decision variables; however, they use simpler deterioration models. Namely, these deterioration models are Markovian, and the state of the Markov chain is limited to the condition of the facility.